REPOGEO REPORT · LITE

serverless/aws-ai-stack

Default branch main · commit 06192019 · scanned 5/20/2026, 3:13:24 AM

GitHub: 1,001 stars · 91 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

35 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 warn · 0 fail

Objective metadata checks

AI knows your name

3 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface serverless/aws-ai-stack, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

highreadme#1

Strengthen README's opening to emphasize production-readiness

Why:

CURRENT

AWS AI Stack – A ready-to-use, full-stack boilerplate project for building serverless AI applications on AWS.

COPY-PASTE FIX

AWS AI Stack – A robust, production-ready, full-stack boilerplate project for building serverless AI applications on AWS.

highlicense#2

Add a LICENSE file to the repository

Why:

COPY-PASTE FIX

Create a `LICENSE` file in the repository root with your chosen open-source license (e.g., MIT, Apache-2.0).

mediumtopics#3

Add topics emphasizing boilerplate and specific AI application types

Why:

CURRENT

aws, aws-bedrock, aws-lambda, claude-ai, full-stack, llama3, serverless, serverless-framework

COPY-PASTE FIX

aws, aws-bedrock, aws-lambda, claude-ai, full-stack, llama3, serverless, serverless-framework, ai-boilerplate, ai-template, chatbot-template, serverless-ai-solution

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface serverless/aws-ai-stack

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Amazon DynamoDB

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

Amazon DynamoDB · recommended 2×
Amazon Cognito · recommended 2×
AWS Lambda · recommended 2×
AWS Amplify Studio · recommended 1×
AppSync GraphQL API · recommended 1×

CATEGORY QUERY
How to quickly build a full-stack serverless AI application on AWS with LLM support?
you: not recommended
AI recommended (in order):
1. AWS Amplify Studio
2. AppSync GraphQL API
3. Amazon DynamoDB
4. Amazon S3
5. Amazon Cognito
6. Amazon Bedrock
7. AWS Lambda
8. Amazon CloudFront
AI recommended 8 alternatives but never named serverless/aws-ai-stack. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Seeking a robust boilerplate for an AI chatbot using serverless architecture and data privacy features.
you: not recommended
AI recommended (in order):
1. AWS Amplify (aws-amplify/amplify-js)
2. Amazon Lex
3. AWS Lambda
4. Amazon DynamoDB
5. Amazon Cognito
6. Google Cloud Dialogflow ES
7. Google Cloud Dialogflow CX
8. Google Cloud Functions
9. Firestore
10. Datastore
11. Microsoft Azure Bot Framework Composer (microsoft/BotFramework-Composer)
12. Azure Cognitive Services
13. Language Understanding - LUIS
14. Azure Functions
15. Azure Cosmos DB
16. Serverless Framework (serverless/serverless)
17. Rasa (RasaHQ/rasa)
18. AWS Fargate
19. Next.js (vercel/next.js)
20. Vercel
21. Supabase (supabase/supabase)
AI recommended 21 alternatives but never named serverless/aws-ai-stack. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
warn
Suggestion:
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of serverless/aws-ai-stack?
pass
AI named serverless/aws-ai-stack explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts serverless/aws-ai-stack in production, what risks or prerequisites should they evaluate first?
pass
AI named serverless/aws-ai-stack explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo serverless/aws-ai-stack solve, and who is the primary audience?
pass
AI named serverless/aws-ai-stack explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of serverless/aws-ai-stack. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/serverless/aws-ai-stack.svg)](https://repogeo.com/en/r/serverless/aws-ai-stack)

HTML

<a href="https://repogeo.com/en/r/serverless/aws-ai-stack"><img src="https://repogeo.com/badge/serverless/aws-ai-stack.svg" alt="RepoGEO" /></a>

Pro

Subscribe to Pro for deep diagnoses

serverless/aws-ai-stack — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite